Enterprise
AI visibility measurement and execution, verifiable by construction.
51% of B2B buyers now start their research in an AI chatbot before Google, up from 29% a year earlier. We measure exactly where each of your brands stands across every engine, publish how we measured it, and ship the fixes ourselves.
Buyer-research figure: G2, The Answer Economy, survey of 1,076 B2B buyers, 2026. Citation-surface figure: ranqo.ai citation-graph study, 149,912 citations across 102 brands and 5 engines, 2026.
Three reasons this holds up under procurement review.
A published, per-engine methodology
Every number traces to a public protocol.
- 7+ runs per prompt, per engine, per day
- 95% confidence interval on every trend
- No blended score: engines share ~12% of sources
Most vendors will not show you the math. Ours is a page anyone can read.
Read the full protocol →Execution where the citations actually live
Only 2.9% of AI citations point to a brand's own site (149,912 citations, 5 engines).
- Wikipedia and Wikidata entity work
- Press placements on vertical publications
- Reddit threads aimed at the queries engines actually run
Tools that only write to your CMS work the smallest lever. We work the other 97%.
See what an execution sprint ships →Data handling that survives security review
Audits run on public information only. We never need access to your customer records.
- No SOC 2 or ISO 27001 claimed. Only what is checkable today
- Full subprocessor list and retention schedule published
- EU-hosted application data, GDPR-native by default
Procurement gets straight answers, not badge walls.
See exactly what we collect →Five components. Combined however your organization actually needs them.
None of this has a fixed price. The self-serve Discovery Audit, Implementation Sprint, and Growth Retainer stay exactly as priced on the pricing page; an enterprise engagement is those same mechanisms run across more brands, more markets, and more engines, scoped on a call.
Multi-brand, multi-market audits
A Discovery Audit run in parallel across every brand in your portfolio and every market you compete in, including language surfaces most tools skip. AI engines often translate a non-English query into English internally before answering it, which changes which sources get cited and structurally disadvantages content that only exists in the local language. Almost nobody checks for this.
Quarterly benchmark
A repeat measurement on the same prompt set and the same engines, so movement is a comparison of confidence bands, not a screenshot next to another screenshot. One cadence across every brand and market you run.
Execution sprints
The same Implementation Sprint mechanism we run self-serve, scoped across your brands and markets: schema deployment, entity work, off-domain placements, then every query re-run to document the delta.
Second-opinion verification
If you already pay for an AI-visibility monitoring dashboard, we are not asking you to rip it out. We run an independent, methodology-disclosed audit alongside it and tell you plainly where the two agree and where they do not.
Agency and in-house enablement
The same white-label pipeline we run for SEO and web agencies, made available to your internal team: your brand on the report, our sampling and execution behind it.